Mathematical models of cognitive processes

The research activity carried out during the PhD course was focused on the development of mathematical models of some cognitive processes and their validation by means of data present in literature, with a double aim: i) to achieve a better interpretation and explanation of the great amount of data obtained on these processes from different methodologies (electrophysiological recordings on animals, neuropsychological, psychophysical and neuroimaging studies in humans), ii) to exploit model predictions and results to guide future research and experiments. In particular, the research activity has been focused on two different projects: 1) the first one concerns the development of neural oscillators networks, in order to investigate the mechanisms of synchronization of the neural oscillatory activity during cognitive processes, such as object recognition, memory, language, attention; 2) the second one concerns the mathematical modelling of multisensory integration processes (e.g. visual-acoustic), which occur in several cortical and subcortical regions (in particular in a subcortical structure named Superior Colliculus (SC)), and which are fundamental for orienting motor and attentive responses to external world stimuli. This activity has been realized in collaboration with the Center for Studies and Researches in Cognitive Neuroscience of the University of Bologna (in Cesena) and the Department of Neurobiology and Anatomy of the Wake Forest University School of Medicine (NC, USA). PART 1. Objects representation in a number of cognitive functions, like perception and recognition, foresees distribute processes in different cortical areas. One of the main neurophysiological question concerns how the correlation between these disparate areas is realized, in order to succeed in grouping together the characteristics of the same object (binding problem) and in maintaining segregated the properties belonging to different objects simultaneously present (segmentation problem). Different theories have been proposed to address these questions (Barlow, 1972). One of the most influential theory is the so called “assembly coding”, postulated by Singer (2003), according to which 1) an object is well described by a few fundamental properties, processing in different and distributed cortical areas; 2) the recognition of the object would be realized by means of the simultaneously activation of the cortical areas representing its different features; 3) groups of properties belonging to different objects would be kept separated in the time domain. In Chapter 1.1 and in Chapter 1.2 we present two neural network models for object recognition, based on the “assembly coding” hypothesis. These models are networks of Wilson-Cowan oscillators which exploit: i) two high-level “Gestalt Rules” (the similarity and previous knowledge rules), to realize the functional link between elements of different cortical areas representing properties of the same object (binding problem); 2) the synchronization of the neural oscillatory activity in the γ-band (30-100Hz), to segregate in time the representations of different objects simultaneously present (segmentation problem). These models are able to recognize and reconstruct multiple simultaneous external objects, even in difficult case (some wrong or lacking features, shared features, superimposed noise). In Chapter 1.3 the previous models are extended to realize a semantic memory, in which sensory-motor representations of objects are linked with words. To this aim, the network, previously developed, devoted to the representation of objects as a collection of sensory-motor features, is reciprocally linked with a second network devoted to the representation of words (lexical network) Synapses linking the two networks are trained via a time-dependent Hebbian rule, during a training period in which individual objects are presented together with the corresponding words. Simulation results demonstrate that, during the retrieval phase, the network can deal with the simultaneous presence of objects (from sensory-motor inputs) and words (from linguistic inputs), can correctly associate objects with words and segment objects even in the presence of incomplete information. Moreover, the network can realize some semantic links among words representing objects with some shared features. These results support the idea that semantic memory can be described as an integrated process, whose content is retrieved by the co-activation of different multimodal regions. In perspective, extended versions of this model may be used to test conceptual theories, and to provide a quantitative assessment of existing data (for instance concerning patients with neural deficits). PART 2. The ability of the brain to integrate information from different sensory channels is fundamental to perception of the external world (Stein et al, 1993). It is well documented that a number of extraprimary areas have neurons capable of such a task; one of the best known of these is the superior colliculus (SC). This midbrain structure receives auditory, visual and somatosensory inputs from different subcortical and cortical areas, and is involved in the control of orientation to external events (Wallace et al, 1993). SC neurons respond to each of these sensory inputs separately, but is also capable of integrating them (Stein et al, 1993) so that the response to the combined multisensory stimuli is greater than that to the individual component stimuli (enhancement). This enhancement is proportionately greater if the modality-specific paired stimuli are weaker (the principle of inverse effectiveness). Several studies have shown that the capability of SC neurons to engage in multisensory integration requires inputs from cortex; primarily the anterior ectosylvian sulcus (AES), but also the rostral lateral suprasylvian sulcus (rLS). If these cortical inputs are deactivated the response of SC neurons to cross-modal stimulation is no different from that evoked by the most effective of its individual component stimuli (Jiang et al 2001). This phenomenon can be better understood through mathematical models. The use of mathematical models and neural networks can place the mass of data that has been accumulated about this phenomenon and its underlying circuitry into a coherent theoretical structure. In Chapter 2.1 a simple neural network model of this structure is presented; this model is able to reproduce a large number of SC behaviours like multisensory enhancement, multisensory and unisensory depression, inverse effectiveness. In Chapter 2.2 this model was improved by incorporating more neurophysiological knowledge about the neural circuitry underlying SC multisensory integration, in order to suggest possible physiological mechanisms through which it is effected. This endeavour was realized in collaboration with Professor B.E. Stein and Doctor B. Rowland during the 6 months-period spent at the Department of Neurobiology and Anatomy of the Wake Forest University School of Medicine (NC, USA), within the Marco Polo Project. The model includes four distinct unisensory areas that are devoted to a topological representation of external stimuli. Two of them represent subregions of the AES (i.e., FAES, an auditory area, and AEV, a visual area) and send descending inputs to the ipsilateral SC; the other two represent subcortical areas (one auditory and one visual) projecting ascending inputs to the same SC. Different competitive mechanisms, realized by means of population of interneurons, are used in the model to reproduce the different behaviour of SC neurons in conditions of cortical activation and deactivation. The model, with a single set of parameters, is able to mimic the behaviour of SC multisensory neurons in response to very different stimulus conditions (multisensory enhancement, inverse effectiveness, within- and cross-modal suppression of spatially disparate stimuli), with cortex functional and cortex deactivated, and with a particular type of membrane receptors (NMDA receptors) active or inhibited. All these results agree with the data reported in Jiang et al. (2001) and in Binns and Salt (1996). The model suggests that non-linearities in neural responses and synaptic (excitatory and inhibitory) connections can explain the fundamental aspects of multisensory integration, and provides a biologically plausible hypothesis about the underlying circuitry.

New markov chain based methods for single and cross-domain sentiment classification

Nowadays communication is switching from a centralized scenario, where communication media like newspapers, radio, TV programs produce information and people are just consumers, to a completely different decentralized scenario, where everyone is potentially an information producer through the use of social networks, blogs, forums that allow a real-time worldwide information exchange. These new instruments, as a result of their widespread diffusion, have started playing an important socio-economic role. They are the most used communication media and, as a consequence, they constitute the main source of information enterprises, political parties and other organizations can rely on. Analyzing data stored in servers all over the world is feasible by means of Text Mining techniques like Sentiment Analysis, which aims to extract opinions from huge amount of unstructured texts. This could lead to determine, for instance, the user satisfaction degree about products, services, politicians and so on. In this context, this dissertation presents new Document Sentiment Classification methods based on the mathematical theory of Markov Chains. All these approaches bank on a Markov Chain based model, which is language independent and whose killing features are simplicity and generality, which make it interesting with respect to previous sophisticated techniques. Every discussed technique has been tested in both Single-Domain and Cross-Domain Sentiment Classification areas, comparing performance with those of other two previous works. The performed analysis shows that some of the examined algorithms produce results comparable with the best methods in literature, with reference to both single-domain and cross-domain tasks, in $2$-classes (i.e. positive and negative) Document Sentiment Classification. However, there is still room for improvement, because this work also shows the way to walk in order to enhance performance, that is, a good novel feature selection process would be enough to outperform the state of the art. Furthermore, since some of the proposed approaches show promising results in $2$-classes Single-Domain Sentiment Classification, another future work will regard validating these results also in tasks with more than $2$ classes.

Efficacy of quality criteria to identify potentially harmful information: a cross-sectional survey of complementary and alternative medicine web sites.

BACKGROUND: Many users search the Internet for answers to health questions. Complementary and alternative medicine (CAM) is a particularly common search topic. Because many CAM therapies do not require a clinician's prescription, false or misleading CAM information may be more dangerous than information about traditional therapies. Many quality criteria have been suggested to filter out potentially harmful online health information. However, assessing the accuracy of CAM information is uniquely challenging since CAM is generally not supported by conventional literature. OBJECTIVE: The purpose of this study is to determine whether domain-independent technical quality criteria can identify potentially harmful online CAM content. METHODS: We analyzed 150 Web sites retrieved from a search for the three most popular herbs: ginseng, ginkgo and St. John's wort and their purported uses on the ten most commonly used search engines. The presence of technical quality criteria as well as potentially harmful statements (commissions) and vital information that should have been mentioned (omissions) was recorded. RESULTS: Thirty-eight sites (25%) contained statements that could lead to direct physical harm if acted upon. One hundred forty five sites (97%) had omitted information. We found no relationship between technical quality criteria and potentially harmful information. CONCLUSIONS: Current technical quality criteria do not identify potentially harmful CAM information online. Consumers should be warned to use other means of validation or to trust only known sites. Quality criteria that consider the uniqueness of CAM must be developed and validated.

Breast cancer on the world wide web: cross sectional survey of quality of information and popularity of websites.

OBJECTIVES: To determine the characteristics of popular breast cancer related websites and whether more popular sites are of higher quality. DESIGN: The search engine Google was used to generate a list of websites about breast cancer. Google ranks search results by measures of link popularity---the number of links to a site from other sites. The top 200 sites returned in response to the query "breast cancer" were divided into "more popular" and "less popular" subgroups by three different measures of link popularity: Google rank and number of links reported independently by Google and by AltaVista (another search engine). MAIN OUTCOME MEASURES: Type and quality of content. RESULTS: More popular sites according to Google rank were more likely than less popular ones to contain information on ongoing clinical trials (27% v 12%, P=0.01 ), results of trials (12% v 3%, P=0.02), and opportunities for psychosocial adjustment (48% v 23%, P<0.01). These characteristics were also associated with higher number of links as reported by Google and AltaVista. More popular sites by number of linking sites were also more likely to provide updates on other breast cancer research, information on legislation and advocacy, and a message board service. Measures of quality such as display of authorship, attribution or references, currency of information, and disclosure did not differ between groups. CONCLUSIONS: Popularity of websites is associated with type rather than quality of content. Sites that include content correlated with popularity may best meet the public's desire for information about breast cancer.

Automatic estimation of noise parameters in Fourier-domain optical coherence tomography cross sectional images using statistical information

We present an application and sample independent method for the automatic discrimination of noise and signal in optical coherence tomography Bscans. The proposed algorithm models the observed noise probabilistically and allows for a dynamic determination of image noise parameters and the choice of appropriate image rendering parameters. This overcomes the observer variability and the need for a priori information about the content of sample images, both of which are challenging to estimate systematically with current systems. As such, our approach has the advantage of automatically determining crucial parameters for evaluating rendered image quality in a systematic and task independent way. We tested our algorithm on data from four different biological and nonbiological samples (index finger, lemon slices, sticky tape, and detector cards) acquired with three different experimental spectral domain optical coherence tomography (OCT) measurement systems including a swept source OCT. The results are compared to parameters determined manually by four experienced OCT users. Overall, our algorithm works reliably regardless of which system and sample are used and estimates noise parameters in all cases within the confidence interval of those found by observers.

Post-colonial (American?) English Presence on the North-Western Pacific Island of Kosrae: A cross-linguistic analysis of the overlaps and divergences of Kosraean English compared to standard American English

Kosrae is the most remote island of the Federated States of Micronesia (FSM), with a population of less than 7,000 inhabitants, located in the Pacific Ocean between Hawaii and Guam. FSM is an independent sovereign nation consisting of four states in total: Pohnpei, Chuuk, Yap, and Kosrae. Having passed through the hands of Spain, Germany and Japan, the United States gained administrative control of FSM after WWII, as commissioned by the UN. The FSM became an independent nation in 1986 while still retaining affiliation with the US under a ‘Compact of Free Association’. Now both Kosraean and English are considered to be the two official languages and the variety of Kosraean English which has arisen proves for an interesting comparative study. In order to obtain the relevant data, I spent three months on the island of Kosrae, interviewing 90 local speakers, ranging in age (16-70), occupation, sex and time spent off island. The 45 minute long interviews were informal but supported by participant information to capture relevant data and conversations were guided in a way that aimed to reveal language and cultural attitudes. With reference to these samples, I examine the effects of American English on the language use in Kosrae. This paper aims to present a broad analysis of phonological, morphosyntactic and pragmatic features, such as pro-dropping, discourse markers and other practices in order to demonstrate the similarities and differences between the two varieties, which are coming to shape the variety developing on Kosrae. Having transcribed conversations using the tool Elan, I will put particular focus on [h] deletion and insertion, a rare occurrence found in a variety of post-colonial American English which I believe is of particular interest. I assess the presence of English in Kosrae with reference to sociological influences, past and present. First, I discuss the extralinguistic factors which have shaped the English that is currently used on Kosrae, including migration between US and FSM, and English as a language of administration, social media usage and visual media presence. Secondly, I assess the use of English in this community in light of Schneider’s (2007) ‘Dynamic Model’, with reference to America’s contribution as an ‘exploitation colony’ as defined by Mufwene (2001). Finally, an overview of the salient linguistic characteristics of Kosraean English, based on the data collected will be presented and compared to features associated with standard American English in view of examining overlap and divergence. The overall objective is to present a cross-linguistic description of a hitherto unexamined English emerging in a postcolonial environment with a juxtaposed contact variety. Mufwene, Salikoko S. 2001. The ecology of language evolution. Cambridge: Cambridge University Press. Schneider, E. (2007). Postcolonial Englishes. Cambridge: Cambridge University Press. Segal, H.G. (1989) Kosrae, The Sleeping Lady Awakens. Kosrae: Kosrae Tourist Division, Dept. Of Conservation and Development. Keywords: American English, Global English, Pacific English, Morphosyntactic, Phonological, Variation, Discourse

Information-Centric Content Retrieval for Delay-Tolerant Networks

The shift from host-centric to information-centric networking (ICN) promises seamless communication in mobile networks. However, most existing works either consider well-connected networks with high node density or introduce modifications to {ICN} message processing for delay-tolerant Networking (DTN). In this work, we present agent-based content retrieval, which provides information-centric {DTN} support as an application module without modifications to {ICN} message processing. This enables flexible interoperability in changing environments. If no content source can be found via wireless multi-hop routing, requesters may exploit the mobility of neighbor nodes (called agents) by delegating content retrieval to them. Agents that receive a delegation and move closer to content sources can retrieve data and return it back to requesters. We show that agent-based content retrieval may be even more efficient in scenarios where multi-hop communication is possible. Furthermore, we show that broadcast communication may not be necessarily the best option since dynamic unicast requests have little overhead and can better exploit short contact times between nodes (no broadcast delays required for duplicate suppression).

Does gender-fair language pay off? The social perception of professions from a cross-linguistic perspective

In many languages, masculine forms (e.g., German Lehrer, “teachers, masc.”) have traditionally been used to refer to both women and men, although feminine forms are available, too. Feminine-masculine word pairs (e.g., German Lehrerinnen und Lehrer, “teachers, fem. and teachers, masc.”) are recommended as gender-fair alternatives. A large body of empirical research documents that the use of gender-fair forms instead of masculine forms has a substantial impact on mental representations. Masculine forms activate more male representations even when used in a generic sense, whereas word pairs (e.g., German Lehrerinnen und Lehrer, “teachers, fem. and teachers, masc.”) lead to a higher cognitive inclusion of women (i.e., visibility of women). Some recent studies, however, have also shown that in a professional context word pairs may be associated with lesser status. The present research is the first to investigate both effects within a single paradigm. A cross-linguistic (Italian and German) study with 391 participants shows that word pairs help to avoid a male bias in the gender-typing of professions and increase women's visibility; at the same time, they decrease the estimated salaries of typically feminine professions (but do not affect perceived social status or competence). This potential payoff has implications for language policies aiming at gender-fairness.

Barriers to cross-border research projects: A prelude to improving professional collaborations between the United States and Mexico

Study objective. This was a secondary data analysis of a study designed and executed in two phases in order to investigate several questions: Why aren't more investigators conducting successful cross-border research on human health issues? What are the barriers to conducting this research? What interventions might facilitate cross-border research? ^ Methods. Key informant interviews and focus groups were used in Phase One, and structured questionnaires in Phase Two. A multi-question survey was created based on the findings of focus groups and distributed to a wider circle of researchers and academics for completion. The data was entered and analyzed using SPSS software. ^ Setting. El Paso, TX located on the U.S-Mexico Border. ^ Participants. Individuals from local academic institutions and the State Department of Health. ^ Results. From the transcribed data of the focus groups, eight major themes emerged: Political Barriers, Language/Cultural Barriers, Differing Goals, Geographic Issues, Legal Barriers, Technology/Material Issues, Financial Barriers, and Trust Issues. Using these themes, the questionnaire was created. ^ The response rate for the questionnaires was 47%. The largest obstacles revealed by this study were identifying a funding source for the project (47% agreeing or strongly agreeing), difficulties paying a foreign counterpart (33% agreeing or strongly agreeing) and administrative changes in Mexico (31% agreeing or strongly agreeing). ^ Conclusions. Many U.S. investigators interested in cross-border research have been discouraged in their efforts by varying barriers. The majority of respondents in the survey felt financial issues and changes in Mexican governments were the most significant obstacles. While some of these barriers can be overcome simply by collaboration among motivated groups, other barriers may be more difficult to remove. Although more evaluation of this research question is warranted, the information obtained through this study is sufficient to support creation of a Cross-Border Research Resource Manual to be used by individuals interested in conducting research with Mexico. ^

Evaluation of a User-Adapted Spoken Language Dialogue System: Measuring the Relevance of the Contextual Information Sources

We present an evaluation of a spoken language dialogue system with a module for the management of userrelated information, stored as user preferences and privileges. The flexibility of our dialogue management approach, based on Bayesian Networks (BN), together with a contextual information module, which performs different strategies for handling such information, allows us to include user information as a new level into the Context Manager hierarchy. We propose a set of objective and subjective metrics to measure the relevance of the different contextual information sources. The analysis of our evaluation scenarios shows that the relevance of the short-term information (i.e. the system status) remains pretty stable throughout the dialogue, whereas the dialogue history and the user profile (i.e. the middle-term and the long-term information, respectively) play a complementary role, evolving their usefulness as the dialogue evolves.

Cross-lingual ontology matching as a challenge for the Multilingual Semantic Web

Recently, the Semantic Web has experienced significant advancements in standards and techniques, as well as in the amount of semantic information available online. Nevertheless, mechanisms are still needed to automatically reconcile information when it is expressed in different natural languages on the Web of Data, in order to improve the access to semantic information across language barriers. In this context several challenges arise [1], such as: (i) ontology translation/localization, (ii) cross-lingual ontology mappings, (iii) representation of multilingual lexical information, and (iv) cross-lingual access and querying of linked data. In the following we will focus on the second challenge, which is the necessity of establishing, representing and storing cross-lingual links among semantic information on the Web. In fact, in a “truly” multilingual Semantic Web, semantic data with lexical representations in one natural language would be mapped to equivalent or related information in other languages, thus making navigation across multilingual information possible for software agents.

Cross-lingual Linking on the Multilingual Web of Data (position statement)

Recently, the Semantic Web has experienced signi�cant advancements in standards and techniques, as well as in the amount of semantic information available online. Even so, mechanisms are still needed to automatically reconcile semantic information when it is expressed in di�erent natural languages, so that access to Web information across language barriers can be improved. That requires developing techniques for discovering and representing cross-lingual links on the Web of Data. In this paper we explore the different dimensions of such a problem and reflect on possible avenues of research on that topic.